Publication date: 15th December 2025
The ability to dynamically control the electronic band gap in semiconductors is essential for next-generation optoelectronic technologies, ranging from adaptive photodetectors to reconfigurable photovoltaics. However, conventional approaches based on temperature or strain provide only slow or limited tunability. In this talk, I will present a promising strategy for achieving fast, reversible band-gap modulation in anharmonic pervoskite-inspired materials by exciting low-energy polar phonon modes that are strongly coupled to electronic states. Using a combination of ab initio calculations, anharmonic Fröhlich theory, and machine-learning techniques, we engineer polar electron–phonon coupling to tune band-gap renormalization under experimentally accessible electric fields on the order of 1 kV/cm [1]. Our strategy is explicitly applied to highly anharmonic anti-perovskite compounds, which already display a broad range of band-gap and light-absorption₋ spectra as a function of composition [2]. This framework offers an appealing alternative to static chemical or structural modifications, enabling non-thermal, ultrafast, and spatially resolved control of band structures with implications for light-responsive devices, adaptive solar absorbers, and quantum optoelectronic platforms. Overall, this work establishes a general strategy for exploiting anharmonic lattice dynamics in perovskite-inspired materials to achieve on-demand control of electronic properties, bringing the prospect of dynamically reconfigurable semiconductor functionality closer to reality.
C.C. acknowledges support by MICIN/AEI/10.13039/501100011033 under the grants PID2023-146623NB-I00 and PID2023-147469NB-C21 and by the Generalitat de Catalunya under the grants 2021SGR-00343, 2021SGR-01519 and 2021SGR-01411. Computational support was provided by the Red Española de Supercomputación under the grants FI-2025-1-0015, FI-2025-2-0006, FI-2025-2-0028 and FI-2025-3-0004. This work is part of the Maria de Maeztu Units of Excellence Programme CEX2023-001300-M funded by MCIN/AEI (10.13039/501100011033).
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